Conference Papers for Web-University at the chair of Prof. Dr. Christoph Meinel

Here you can find all our peer-reviewed conference papers about Web-University, e-learning, tele-teaching, tele-TASK, MOOCs:

Action Recognition in Surveillance Video Using ConvNets and Motion History Image

Luo, Sheng; Yang, Haojin; Wang, Cheng; Che, Xiaoyin; Meinel, Christoph in Artificial Neural Networks and Machine Learning – ICANN 2016 page 187-195 . Springer , 2016 .

With significant increasing of surveillance cameras, the amount of surveillance videos is growing rapidly. Thereby how to automatically and efficiently recognize semantic actions and events in surveillance videos becomes an important problem to be addressed. In this paper, we investigate the state-of-the-art Deep Learning (DL) approaches for human action recognition, and propose an improved two-stream ConvNets architecture for this task. In particular, we propose to use Motion History Image (MHI) as motion expression for training the temporal ConvNet, which achieved impressive results in both accuracy and recognition speed. In our experiment, we conducted an in-depth study to investigate important network options and compared to the latest deep network for action recognition. The detailed evaluation results show the superior ability of our proposed approach, which achieves state-of-the-art in surveillance video context.
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Further Information
Tags Convolutional_neural_network Motion_History_Image Optical_flow Surveillance_videos its

 

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